(Peer-Reviewed) Structural color: an emerging nanophotonic strategy for multicolor and functionalized applications
Wenhao Wang 王文豪 ¹, Long Wang 王龙 ¹, Qianqian Fu 傅茜茜 ², Wang Zhang 张旺 ³, Liuying Wang 汪刘应 ¹, Gu Liu 刘顾 ¹, Youju Huang 黄又举 ², Jie Huang 黄洁 ¹, Haoyuan Zhang 张淏源 ¹, Fuqiang Guo 郭富强 ¹, Xiaohu Wu 吴小虎 ⁴
¹ Zhijian Laboratory, Rocket Force University of Engineering, Xi'an 710025, China
中国 西安 火箭军工程大学 智剑实验室
² College of Materials, Chemistry and Chemical Engineering, Hangzhou Normal University, Hangzhou 311121, China
中国 杭州 杭州师范大学材料与化学化工学院
³ Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore
⁴ Thermal Science Research Center, Shandong Institute of Advanced Technology, Jinan 250100, China
中国 济南 山东高等技术研究院 热科学研究中心
Opto-Electronic Science, 2025-04-25
Abstract
Color as an indispensable element in our life brings vitality to us and enriches our lifestyles through decorations, indicators, and information carriers. Structural color offers an intriguing strategy to achieve novel functions and endows color with additional levels of significance in anti-counterfeiting, display, sensor, and printing.
Furthermore, structural colors possess excellent properties, such as resistance to extreme external conditions, high brightness, saturation, and purity. Devices and platforms based on structural color have significantly changed our life and are becoming increasingly important. Here, we reviewed four typical applications of structural color and analyzed their advantages and shortcomings. First, a series of mechanisms and fabrication methods are briefly summarized and compared.
Subsequently, recent progress of structural color and its applications were discussed in detail. For each application field, we classified them into several types in terms of their functions and properties. Finally, we analyzed recent emerging technologies and their potential for integration into structural color devices, as well as the corresponding challenges.
Separation and identification of mixed signal for distributed acoustic sensor using deep learning
Huaxin Gu, Jingming Zhang, Xingwei Chen, Feihong Yu, Deyu Xu, Shuaiqi Liu, Weihao Lin, Xiaobing Shi, Zixing Huang, Xiongji Yang, Qingchang Hu, Liyang Shao
Opto-Electronic Advances
2025-11-25
